Remote sensing involves observations made using satellite images and aerial photographs. Remote sensing is used to study, among other things, the quality of surface water, the extent of ice cover, water temperature, and coastal vegetation.
Satellites measure sunlight reflected from water areas or the thermal radiation of the object being studied. Satellite devices take and store images in the same way as regular digital cameras. The difference is that satellite images are taken more precisely and in several narrow wavelength ranges.
Substances in the water, such as clay, humus, or algae particles, reflect light differently at different wavelengths. This is why the human eye sees them in different colors. By interpreting satellite images, information about water quality can be obtained. It is important to monitor, for example, the variation in algae amounts and water turbidity. Mathematical models that combine observations at different wavelengths are used in the interpretation. Nowadays, machine learning methods are often used. The processing and interpretation of satellite observations are mostly automated. True-color images are available on the same day.
Satellite observations are repeatedly obtained from sea areas. It is therefore possible to create time series and deduce trends from them. Composite statistics can also be made from the time series, calculating, for example, the average amount of algae over several years. In Finland, a comprehensive reed bed survey of the entire coastline has also been conducted based on satellite images.
Satellites are valuable tools in ice research. For example, both visible light imaging satellites and radar satellites are used to create ice maps. Algorithms are being developed to interpret radar images, which can calculate ice coverage and thickness. This data is supplemented with so-called mass balance buoys. Radar satellites are particularly important because they can detect through clouds.
The movement and deformation of ice fields have traditionally been studied using both satellite images and buoys drifting with the ice. In recent years, a method utilizing coastal radar observation data has also been developed. Radar data allows for more precise monitoring of ice movements throughout the winter.
Satellite images are not very useful near the shore, where the land causes reflections in the images. However, shallow shores are ecologically particularly interesting, and there are many of them along Finland’s fragmented coastline. Therefore, cameras attached to airplanes or drones are used. These can identify objects as small as a few centimeters, whereas the resolution of satellite images is at best a couple of meters.
Ordinary digital cameras can be used in aerial photography. Depending on the need, multispectral sensors, which capture images in multiple wavelength ranges, or cameras that register thermal radiation are also used. Aerial images can be used to study, for example, shoreline shifts or the spread of coastal wetlands. The advantage of aerial photography is that the atmosphere does not cause errors in the results, and clouds are not an obstacle when flying below the cloud cover.
Remote sensing methods also include LiDAR (Light Detection and Ranging). It is especially used in shallow water areas. In LiDAR imaging, the camera itself sends light to the target and measures the reflected light. From the reflection, it can be determined whether there is deep water, vegetation, or a specific aquatic plant under the water surface.
The wavelength of the light is chosen according to the research needs. Red light cannot penetrate water significantly, so it is used to study the spread of reed beds, for example. Green light, on the other hand, is used to investigate the bottom vegetation of clear and shallow areas and the quality of the seabed.
